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Applied Surface Science 257 (2011) 8864– 8870

Contents lists available at ScienceDirect

Applied Surface Science

jou rn al h om epa g e: www.elsev ier .com/ locate /apsusc

he sputtering properties of artificial polymorphic AB binary compound crystals

.A. Karolewskichool of Education, University of New South Wales, Sydney, NSW 2052, Australia

r t i c l e i n f o

rticle history:eceived 23 January 2011ccepted 22 April 2011vailable online 23 May 2011

eywords:olecular dynamics

putteringlusters

a b s t r a c t

Molecular dynamics (MD) simulations of the sputtering of artificial 1:1 binary compound targets, AB,are reported. The simulations explore the sensitivity of monomer and dimer sputter yields to AB targetstructure and interatomic potentials. The targets have the sphalerite, wurtzite and sodium chloride latticestructures, and their atomic and material properties resemble those of ZnS polymorphs. Two different setsof interatomic potentials were used for the simulations. In the symmetric model, all bonding interactionsare equivalent, while in the asymmetric model, the A–B interactions are strengthened at the expense of theA–A and B–B interactions. Both models predict similar material properties for a given target. No systematicvariations of sputter yields for individual targets can be discerned between the predictions based on thesymmetric and asymmetric interaction models. The relative sputter yields of monomer species A and B

are independent of target structure when the A and B atoms occupy surface sites of equivalent symmetry.The relative yields of the AA and BB dimer species are similarly insensitive to the target structure, buttarget-dependent variations of the relative yields of AB dimers are observed. Sputtering properties otherthan relative yields (e.g. clustering range, depth of origin) do show structure-dependent variations. Inagreement with previous MD studies of sputtering from metals, the nearest-neighbour contribution toAB clusters is found to be typically ∼50%, and may be as low as 30%.

. Introduction

The influence of crystal structure on the sputtering propertiesf compound materials is of fundamental interest for experimentalechniques that exploit the effects of sputtering. The prefer-ntial sputtering of compound targets affects the outcomes ofputter-deposition and ion-milling procedures [1,2]. High precisionecondary ion isotopic ratio measurements on minerals display

crystallographic dependence that is not yet understood [3,4].econdary ion mass spectroscopy (SIMS) speciation analysis deter-ines sample compositions through comparisons of secondary ion

bundance distributions with those from standards [5–9]. WhileIMS spectra have been reported for many kinds of inorganic com-ounds [5,7,10–16], there has been limited progress towards thexplanation or prediction of their secondary ion abundance distri-utions.

Molecular dynamics (MD) simulations provide a method fortudying the effects of material-dependent parameters on sput-ering properties [17,18]. In some of the earliest MD studies onompounds, Garrison et al. [19,20] explored the effects of atomic

ass, surface binding energy and surface structure, on preferential

puttering and cluster formation from ordered metallic overlayers.ades and Urbassek [21] used MD to study the sputtering of ran-

E-mail address: karolewski@alum.mit.edu

169-4332/$ – see front matter © 2011 Elsevier B.V. All rights reserved.oi:10.1016/j.apsusc.2011.04.110

© 2011 Elsevier B.V. All rights reserved.

dom CuX alloys that were related through systematic variationsof the mass and site energy of the alloying component X. The MDresults were then used to test the mass and surface binding energydependence of sputter yields for homogenous alloys, as predictedby Sigmund’s analytic sputtering theory [22]:

YB

YA=

(MA

MB

)2m(UA

UB

)1−2m

(0 ≤ m ≤ 0.2) (1)

Eq. (1) predicts the sputter yield ratio, YA/YB, for two compo-nents A and B that do not differ greatly in their respective masses(MA, MB); UA and UB are the corresponding surface binding ener-gies. The mass dependence given in Eq. (1) was confirmed byGades and Urbassek, but they found the predicted surface bindingenergy dependence to diverge from MD predictions at low pro-jectile energies (<3 keV). Colla and Urbassek [23] concluded thatpreferential sputtering in ordered and random Cu–Au alloys wasmainly due to the mass difference between Cu and Au. For a givenalloy composition, the short range ordering was found to exertonly a minor influence on dimer abundance distributions, whichwere largely determined by statistical recombination factors. MostMD studies of the interplay between the structure and sputtering

behaviour of elements and compounds have employed targets withclose-packed metallic structures. However, Yurasova et al. [24]recently compared the collisional sputtering of B and N atoms fromthree polymorphic BN crystals, including the projectile energy and

ace Science 257 (2011) 8864– 8870 8865

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pairwise interactions.The parameters for the symmetric potentials (Table 1, column

1) were fitted to an AB target having the c-ZnS structure, in orderto reproduce exactly the experimental lattice constant, cohesive

Table 1Morse potential parameters and materials data predicted for the AB target withcubic ZnS (c-ZnS) lattice structure. The cut-off distance for all potentials is 4.000 A.

Symmetric Asymmetric

D (eV) 1.228951 1.065684 (AA, BB)1.598526 (AB)˛ (A−1) 0.911283 0.963010 (AA, BB)0.800000 (AB)r0 (A) 2.927836 2.927836Cohesive energy (eV) 6.31 6.31Bulk modulus (GPa) 75.0 62.6EA–B (eV)a −0.307 −0.512EA–A (eV)b −0.424 −0.355

M.A. Karolewski / Applied Surf

ngular dependence of sputter yields, the spatial origins, energyistribution and Wehner spot patterns.

This paper reports a MD study of the sputtering of artificialinary 1:1 compound targets (designated hereafter by the formulaAB”) that have the sphalerite, wurtzite and sodium chloride lat-ice structures, respectively. Two different, idealized, models of thettractive interatomic forces (based on Morse potentials) are usedo explore how the sputtering properties of monomer and dimerpecies are influenced by structural polymorphism and surface ori-ntation.

The study was undertaken, in part, to shed light on the signifi-ance of structure for SIMS abundance distributions (e.g. in SIMSpeciation analysis). This has been a topic of interest since thenception of SIMS. For example, Buhl and Preisinger sought motifs ofhe original crystal structure in the abundance distributions of sput-ered cluster ions [25], whereas Plog et al. systematized secondaryon abundance distributions from metal oxides in statistical terms10]. The viewpoint of some SIMS practitioners is that (a) clusterons (e.g. MoO+) indicate which atoms are “in contact” in the tar-et, while (b) “fragmentation patterns” (e.g. MoOn

− with n = 0–4)re sometimes characteristic for a specific compound (e.g. MoO3)8]. This study is also motivated by an interest in the use of MDor routine predictions of the collisional sputtering properties ofompounds This is an area that is currently dominated by Montearlo codes such as SRIM [26], due to the specialized knowledgeequired to fit or implement many-body interatomic potentials forompounds. The simulations discussed in this paper employ Morseotentials that can easily be fitted for many 1:1 compounds.

. Computational method

.1. Simulation procedure

Molecular dynamics sputtering simulations were performedsing the Kalypso package (version 3.1) [27]. The 1:1 binary com-ound crystallites (designated by the formula “AB”) that were useds targets in the sputtering simulations were based on the follow-ng lattice structure types: sphalerite (cubic ZnS, or c-ZnS), wurtzitehexagonal ZnS, or h-ZnS) and rocksalt (NaCl). The atomic num-ers and masses of their constituent atoms (A, B) were assigned tohose of zinc (Zn, 65.37) and sulphur (S, 32.06). For convenience,his study identifies the simulated AB targets using their structureypes (e.g. “c-ZnS target”). However, it is emphasized that the sim-lation targets are artificial materials that only reproduce a fewaterial properties of c-ZnS (Section 2.2).Each AB target crystallite consisted of >1.5 × 104 atoms, with

urface edge lengths >80 A and depths >30 A. No vibrational dis-lacements were applied to target atoms. The simulations for eacharget followed 2500 or more projectile (3 keV Ar) incident trajec-ories that were distributed within primary impact zones whoseimensions were determined by the surface symmetry of eacharget. Sputtering simulations were performed for targets withhe following surface orientations, which are depicted in Fig. 1:-ZnS(1 0 0), c-ZnS(1 1 0), h-ZnS(1 0 0) (synonymous with h-ZnS1010) in the Bravais-Miller notation), NaCl(1 0 0), NaCl(1 1 0). Fur-her structural details are given in the next section. In all targets,xcept c-ZnS(1 0 0), the A and B atoms occupy surface lattice sitesith the same symmetry and binding energy.

The projectile bombardment strategy was chosen to minimizehannelling effects: the altitudinal (ϕ) angle of the incident pro-ectile was inclined at 40◦ to the surface, while the azimuthal (�)

ngle of projectile incidence was chosen randomly (within a 45◦

r 90◦ range, according to surface symmetry). Target atoms wereonsidered to be sputtered if they were situated >6 A above theurface (>12 A for the c-ZnS(1 1 0) targets) at the termination of

Fig. 1. Structures of the surfaces of the AB binary compound crystallites used forthe sputtering simulations (atomic positions drawn to scale). The crystallites areviewed from above the surface. Black (grey) spheres represent atoms of A (B) type.

each run (800 fs). Sputtered clusters were identified using Stod-dard’s algorithm [28] with a clustering radius of 4.0 A. Containmentof the active sputtering regions within the simulation lattices wassatisfactory. The small contribution from sputtered edge atoms isexcluded from the sputter yield predictions.

Projectile interactions with atoms in the simulation targets weredescribed using uncorrected ZBL potentials based on the atomicnumbers of Zn and S (for A and B type atoms respectively). Morseinteratomic potentials were used to represent the attractive inter-atomic forces between atoms of the AB target crystallites (the fittingprocedure is discussed below). To further stabilize the simulationcrystallites, the two outermost layers (one layer for NaCl latticetypes) of atoms at the crystallite edges were, in addition, bound totheir lattice sites by harmonic springs (force constants 3 eV A−2;springs were snapped permanently if the atomic kinetic energyexceeded 3 eV). The Morse potentials were joined smoothly to ZBLpotentials in the core region by means of an interpolating func-tion applied in the region 1.35–1.90 A, and were truncated above4.000 A (between second and third neighbour distances) using acut-off switching function applied in the region 3.823–4.000 A.

2.2. Attractive interatomic potentials

Two different sets of potentials (designated hereafter as “sym-metric” and “asymmetric” potentials, respectively) were developedfor use in the simulations. The potentials differ in terms of howthe interatomic forces are distributed among the various possible

a EA–B denotes the mutual potential energy of atoms of type A and B that arenearest neighbours.

b EA–A denotes the mutual potential energy of two atoms of type A that are next-nearest neighbours. Note that EA–A = EB–B in all simulations.

8866 M.A. Karolewski / Applied Surface Science 257 (2011) 8864– 8870

Table 2Selected material and structural properties of AB simulation targets predicted bythe symmetric and asymmetric Morse potentials (for c-ZnS and h-ZnS targets, thelisted properties are identical for both potentials).

Structure c-ZnS h-ZnS NaCl

Equilibrium latticeparameters (A)

5.4053 3.8221 (a),6.2415 (c)

5.0088a, 5.0132b

Density (g cm−3) 4.098 4.098 5.150a, 5.136b

R1 (A)c 2.341 (×4) 2.341 (×4) 2.5044a, 2.5066b (×6)R2 (A)c 3.822 (×12) 3.822 (×12) 3.5418a, 3.5449b (×12)Cohesive energy(eV)

6.31 6.31 8.89a, 9.14b

a Using symmetric Morse potential.

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Table 3Surface binding energies (unrelaxed) predicted by symmetric and asymmetricMorse potentials for simulation crystallites. The same values apply to both A andB type atoms in the crystallite, except where noted.

Crystallite type Surface binding energy (eV)

Symmetric potential Asymmetric potential

c-ZnS(1 0 0) 8.00 (A), 9.23 (B) 7.73 (A), 9.78 (B)c-ZnS(1 1 0) 7.77 8.04

The predicted monomer and dimer sputter yields (Y1 and Y2)are typically ∼2 and ∼0.03 respectively. The predicted dimer tomonomer ratios Y2/Y1 have a narrow distribution (1.1 ± 0.2 × 10−3)for the different target-potential combinations. Sputtered trimer

Table 4“Total” sputter yields (Y), and disaggregated sputter yields, for type A (YA) and typeB (YB) atomic components, and for monomer (Y1), and dimer (Y2) species, that werepredicted for the different target-potential combinations. Typical errors in sputteryields are ±2–3%, except for Y2 (±13%).

Lattice and potentiala Y YA YB Y1 Y2 Y2/Y1 (×103)

c-ZnS(1 0 0)Symm. 2.16 1.20 0.97 2.12 0.020 9.4Asymm. 2.31 1.32 0.99 2.24 0.029 13

c-ZnS(1 1 0)Symm. 2.54 1.05 1.49 2.50 0.019 7.6Asymm. 2.67 1.14 1.53 2.62 0.023 8.6

h-ZnS(1 0 0)Symm. 2.46 1.04 1.42 2.43 0.018 7.4Asymm. 2.46 1.05 1.41 2.41 0.027 11

NaCl(1 0 0)Symm. 2.51 1.09 1.42 2.44 0.032 13Asymm. 2.49 1.06 1.43 2.43 0.029 12

NaCl(1 1 0)

b Using asymmetric Morse potential.c R1 (R2): first (second) nearest neighbour distance (the coordination number for

ach shell is indicated in parentheses).

nergy and bulk modulus of sphalerite. Identical Morse pair poten-ials, V(r), were used for each of the three distinct types of pairwisenteraction (A–A, B–B, A–B):

(r) = D (exp (−2˛ [r − r0]) − 2 exp (−˛ [r − r0])) (2)

The parameters for the asymmetric set of potentials (Table 1,olumn 2) were obtained by modifying those for the symmetricotential in a manner that left the predicted cohesive energy and

attice constant for the c-ZnS lattice unchanged. The D parametersor the homonuclear (A–A, B–B) and heteronuclear (A–B) interac-ions were adjusted in opposite directions, such that the AB dimerinding energy (BE) would be 50% greater than the AA and BB dimerEs. A common adjustment was made to the parameter in ordero facilitate smooth interpolation to the ZBL potential, while alsonsuring that the A–B interactions were more attractive than the–A or B–B interactions in the equilibrium lattice structure. Due to

hese parameter changes, the predicted bulk modulus for the c-ZnSattice was reduced by 17%.

In summary, for both sets of potentials the A–A and B–B interac-ions are energetically equivalent. The A–B interactions are eitherquivalent to the A–A and B–B interactions (symmetric potentials),r more attractive by 50% (asymmetric potentials). Table 2 reportsome structural and material properties predicted for the variousombinations of simulation crystallite and Morse potentials. Theattice parameters and cohesive energies of the c-ZnS and h-ZnS tar-ets are identical for both potentials, and differ by only 0.1% and 3%,espectively, for the NaCl targets. The h-ZnS simulation crystalliteas the ideal c/a ratio, and has first and second neighbour coor-ination geometries that are identical to those of the c-ZnS lattice.he lattice parameters predicted for the NaCl simulation crystallitesa = 5.009–5.013 A) are close to the experimental value for the high-ressure (15 GPa) rocksalt (B1) phase of ZnS (a = 5.13 ± 0.08 A) [29].he predicted cohesive energies for the NaCl crystallites are 41–45%reater than those of the c-ZnS and h-ZnS crystallites, due to morefficient atomic packing, whereas in reality the cohesive energy of1-ZnS is ∼15% lower than that of the zincblende structure [29].

The A and B atoms at the c-ZnS(1 0 0) surface reside in distincttructural environments that are associated with different surfaceinding energies. The surface binding energy is the energy cost toemove a surface atom from the ideal target lattice. This quantity isarger than the cohesive energy [30]. The predicted values that areelevant for the present study are listed in Table 3. The predictedurface binding energies for the artificial c-ZnS(1 1 0) AB targetange between 7.8 and 8.0 eV. For real c-ZnS(1 1 0) the (relaxed) sur-ace binding energies are 5.3 eV (Zn vacancy) and 6.7 eV (S vacancy)31].

Morse potentials stabilize close-packed lattices. Reconstructionf the metastable simulation crystallites used in this work takes theorm of an amorphous compression that commences near projec-ile and recoil tracks in the cooling phase of the collision cascade

h-ZnS(1 0 0) 9.26 9.66NaCl(1 0 0) 12.81 13.52NaCl(1 1 0) 10.85 11.33

after about 300 fs. Thus, the simulations do not provide a usefuldescription of the relaxation processes that take place in the tar-get after 300 fs. However, this timescale is longer than that typicallyrequired for sputtering, which is 90% complete after 200 fs, and 95%complete after 300 fs.

3. Results

3.1. Sputter yields

Table 4 reports the partial sputter yields for components A andB (YA, YB), monomer (Y1), and dimer (Y2) species that were pre-dicted for the different target-potential combinations. The “total”sputter yields (Y = YA + YB) are also reported. The YB/YA ratio fallsin the narrow range 1.42 ± 0.14 for both symmetric and asym-metric potentials, and for all targets in which the A and B atomsoccupy structurally equivalent sites (i.e. excluding c-ZnS(1 0 0) tar-gets). This ratio represents the degree of preferential sputteringdue to mass differences between A and B atoms. The MD pre-dictions correspond to m ≈ 0.25 in Sigmund’s sputtering theory,Eq. (1) (which does not strictly apply to the AB targets, whichhave large mass ratios MA/MB = 2.0). The YB/YA ratio of 1.42 ± 0.14obtained in this work for AB targets is similar to the ratio of 1.30predicted for the corresponding sputter yield ratio of an artificial63Cu126Cu alloy with the same constituent mass ratio [21]. For poly-morphic BN targets with a lower constituent mass ratio of 1.3,Yurasova et al. obtained sputter yield ratios in the range 1.10–1.30[24].

Symm. 1.83 0.80 1.03 1.80 0.016 8.9Asymm. 1.74 0.74 1.00 1.70 0.019 11

a The designations Symm. and Asymm. refer to simulations that employ the sym-metric and asymmetric Morse potentials, respectively.

ace Science 257 (2011) 8864– 8870 8867

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M.A. Karolewski / Applied Surf

ields are not reported in Table 4 because they were too low (typ-cally ≤10−3) to provide reliable estimates of the mean sputterields. The sputter yields reported in Table 4 are an order of mag-itude below those for typical metals, due to the high cohesivenergies and low densities of the target materials (which are rep-esentative of third period metal sulphides).

It is also of interest to compare the sputter yield predictionsor the h-ZnS targets with experimental values that are availableor single crystal h-ZnS (wurtzite, orientation unspecified). Theotal sputter yield (Y = YZn + YS) was estimated to be 1.4 for nor-

ally incident 3 keV Ar+ bombardment in Ref. [32], correspondingo Y ≈ 2.2 at ϕ = 40◦ (assuming a 1/sin ϕ dependence). The pre-icted value for the h-ZnS(1 1 0) target (Y = 2.5) is close to thisalue (Table 4). However, Ref. [32] estimates that Y2/YZn > 0.11,hich is one order of magnitude above the corresponding predic-

ion for the model h-ZnS(1 1 0) target (Y2/YA ∼ 0.01). The primaryollision cascade development in covalent and ionic materialss mainly determined by short range forces. Simulations of thisrocess are tolerant to the form of the attractive part of the inter-tomic potential [33]. In the simulation model, the dissociationnergies of sputtered dimers lie between 1.1 and 1.6 eV (Morseotential D parameters, Table 1). However, the experimental val-es of the dissociation energies for dimers sputtered from ZnS all

ie outside this range: 0.17 eV (Zn2), 2.1 eV (ZnS) and 4.4 eV (S2)32].

No systematic variations of sputter yields for individual targetsan be discerned between the predictions based on the symmet-ic and asymmetric interaction models. Sigmund’s theory (Eq. (2))redicts a sputter yield enhancement of ∼4% on changing from thesymmetric to the symmetric potential due to differences in theurface binding energy (see data in Table 3). This small enhance-ent factor is comparable to the statistical error (3%) of the MD

ield predictions.The absolute sputter yields of the individual target components

ary by almost a factor of 2 (YA: 0.74–1.32; YB: 0.99–1.80) betweenhe various targets. Differences in the packing densities of crystalayers (which determines the characteristics of projectile nucleartopping) and the cohesive energies are major contributors to thisariation. Since the influence of these factors on sputter yields isifficult to separate from the effects of structure, the remainder ofhis paper will compare monomer and dimer sputtering propertiesn terms of abundance distributions (normalised relative sputterields).

.2. Sputtered monomers

The predicted abundances of A and B monomers, expresseds percentages of the total monomer sputter yield, are comparedor the different combinations of targets and potentials (symmet-ic/asymmetric) in Fig. 2. For all such combinations, except thosehat involve the c-ZnS(1 0 0) target, preferential sputtering of theighter monomer species (B) takes place, such that the A atomsontribute only 39–43% of the monomer sputter yield. This resultemonstrates that in targets where A and B atoms occupy struc-urally and energetically equivalent sites, the abundance ratio ofputtered monomers is dependent on atomic mass, but indepen-ent of both target structure and the form of the interatomicotential. In contrast, the heavier A atoms are preferentially sput-ered for the c-ZnS(1 0 0) target. This effect originates from theocation of type A atoms at the surface of this target (Fig. 1), where

hey have a lower surface binding energy (Table 3) and are less hin-ered than B atoms below the surface. For this target, the monomerelative abundances again show no significant dependence on theorm of the interatomic potential.

Fig. 2. Sputtered monomer (A, B) and dimer (AA, BB, AB) relative abundances, pre-dicted using symmetric and asymmetric Morse potentials, for various surfaces of ABsimulation targets having the c-ZnS, h-ZnS and NaCl lattice structures.

3.3. Sputtered dimers

Dimer abundance distributions (the abundances of AA, BB andAB dimers, expressed as percentages of the total dimer sput-ter yield) are compared for the different combinations of targetsand interaction models (symmetric/asymmetric) in Fig. 2. In mostcases, the dimer abundances follow the order AA < BB < AB. The c-ZnS(1 0 0) target (with asymmetric potentials) was the only systemfor which the AA abundance exceeded that of BB, presumably due tothe structural inequivalence of A and B sites in this target. As shownin Fig. 1, the first monolayer of the c-ZnS(1 0 0) target consists of Aatoms, while B atoms are located only in sub-surface lattice sites.The preferential sputtering of BB relative to AA for the remainingsystems resembles the preferential sputtering behaviour of the cor-responding (B, A) monomer species (Section 3.2). For all targets, theAB abundance increases (by 23–61%) when the asymmetric poten-tial is used, probably because this potential stabilizes AB clustersrelative to AA and BB clusters.

Fig. 3 provides information about the separations of the origi-nal lattice sites of the pairs of atoms that are sputtered as dimers(“clustering distance”). AA and BB dimers are comprised of atomsthat were not nearest neighbours in the original crystallite. There isthus no reason to expect that the constituents of AB dimers shouldbe confined to neighbouring atoms. Fig. 3 shows that typically abouthalf of the AB dimers are formed from neighbouring atoms. How-ever, the clustering behaviour varies from target to target, and alsoshows significant variations with the interatomic potential. Similarfractions of AA and BB dimers are formed from the lattice next-

nearest neighbours (except for the c-ZnS(1 0 0) target), showingthat atomic mass has little influence on the dimer clustering range.

Fig. 4 plots the site–site tilt angles (ˇ) for pairs of atoms thatare sputtered as dimers. This angle measures the inclination of a

8868 M.A. Karolewski / Applied Surface Science 257 (2011) 8864– 8870

Fig. 3. The predicted proportions of sputtered dimers (AA, BB, AB) whose con-stituents originate from first nearest neighbour (1NN) or second nearest neighbour(mc

lsalaˇ

ctpdthanin

4

stcnstci

9060300Site-site tilt angle (°)

0

0.4

0.80

0.4

0.80

0.4

0.8

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ativ

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quen

cy 0

0.4

0.80

0.4

0.8

9060300

c-ZnS(100)

c-ZnS(110)

h-ZnS(100)

NaCl(100)

NaCl(110)

AsymmetricSymmetric

Fig. 4. Site–site tilt angles for constituents of sputtered dimers. A tilt angle of 0◦

(90◦) indicates that the atoms in the dimer originate from sites in the same hori-

2NN) sites in the undisturbed AB simulation targets. Predictions based on the sym-etric and asymmetric Morse potentials, are shown for various surfaces having the

-ZnS, h-ZnS and NaCl lattice structures.

ine joining the two lattice sites, relative to the plane of the targeturface. The value = 0◦ indicates that the dimer was formed fromtoms that were originally at the same target depth (e.g. surfaceayer atoms). Fig. 4 indicates that >80% dimers are formed fromtoms derived from lattice sites that are coplanar or inclined with

< 45◦.Fig. 5 plots the depth of origin predicted for the atomic

onstituents of dimers sputtered from the various targets. Quali-atively similar behaviour is predicted for both sets of interatomicotentials. For the NaCl targets, sputtered dimers originate pre-ominantly (≥76%) from atoms located in the surface layer of thearget. For the c-ZnS(1 0 0) and h-ZnS(1 1 0) lattice types, whichave no nearest neighbours that also lie in the surface plane (Fig. 1),bout half (44–55%) of the constituents of sputtered dimers origi-ate from sub-surface target layers. The c-ZnS(1 1 0) surface shows

ntermediate behaviour. The sub-surface contribution is most pro-ounced for the c-ZnS(1 0 0) lattice type.

. Discussion

The simulations explore the sensitivity of monomer and dimerputter yields to AB target structure and interatomic potential. Thearget composition and bulk cohesive energy are maintained atonstant values through the simulations. The simulations makeo provision for non-collisional sputtering processes, which may

trongly enhance sputtering in some types of compounds, such ashose that contain volatile components [34,35]. In all targets except-ZnS(1 0 0), the A and B atoms occupy sites of equivalent symmetryn the surface and bulk (for c-ZnS(1 0 0), the A and B atoms occupy

zontal (vertical) plane. Predictions based on the symmetric and asymmetric Morsepotentials, are shown for various surfaces having the c-ZnS, h-ZnS and NaCl latticestructures.

equivalent bulk sites only). The equivalence of A and B site symme-tries is typical for the most common 1:1 compounds that belongto the cubic or hexagonal crystal systems (NaCl, c-ZnS, h-ZnS, CsCl,NiAs). The bonding interactions in the simulation targets producedby the symmetric interaction model are equivalent to those of iso-topically structured crystals (albeit with gross mass differences).The asymmetric interaction model strengthens the A–B attractionat the expense of the A–A and B–B attractions.

Fig. 2 indicates that the relative yields of sputtered monomerspecies A and B are independent of target structure when the Aand B atoms occupy surface sites of equivalent symmetry (i.e. allcases except the c-ZnS(1 1 0) lattice type). The relative yields of thedimer species are similarly insensitive to the structural environ-ment, except for c-ZnS(1 1 0) which produces AB dimers in lowerabundance than the other systems. This cannot be rationalized asan effect of the immediate structural environment alone, becausetypically only <50% of AB dimers are formed between atoms at firstneighbour lattice sites. The fraction of all dimers formed betweennearest-neighbours is typically <30% for the various AB targets,which is somewhat lower than the 50–60% predicted in MD sput-tering simulations for metals [21,23,36–38]. This is probably astatistical effect due the higher secondary to primary coordina-tion number ratios (N2:N1) for surface atoms in the AB targets(N2:N1 = 1.6–4.0), compared with the same ratio (∼0.6) in close-packed metals.

The fraction of dimer constituents derived from the surface layershows a marked dependence on the crystallographic structure of

the near-surface layers (Fig. 5), but mechanistic differences in thisrespect do not necessarily result in distinctive abundance distribu-tions (e.g. the NaCl(1 0 0) and h-ZnS(1 0 0) lattices display almostidentical dimer abundance distributions in Fig. 2, although they

M.A. Karolewski / Applied Surface Sc

0-3-6-9

Depth of origin (Å)

0

40

80 c-ZnS(100)

0

40

80

h-ZnS(100)

0

40

80

Rel

ativ

e yi

eld

(%)

c-ZnS(110)

0

40

80 NaCl(100)

0

40

80 NaCl(110)

AB

0-3-6-9

AB

AsymmetricSymmetric

Fig. 5. Depth of origin (z) of the constituents of sputtered dimers for AB targets (thetarget interior corresponds to z < 0). Predictions based on the symmetric and asym-mNf

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l2ftouBytfTspd

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etric Morse potentials, are shown for various surfaces having the c-ZnS, h-ZnS andaCl lattice structures. The c-ZnS(1 0 0) data are disaggregated into contributions

rom atoms of type A and B (black and white bars, respectively).

iffer significantly in terms of their surface contributions, Fig. 5).he structure of the c-ZnS target is related to that of silicon. The vari-tion in depth of origin of sputtered atoms for the (1 0 0) and (1 1 0)urfaces of the c-ZnS targets resembles what has been observed inD simulations of sputtering from the (1 0 0) and (1 1 0) surfaces

f Si [39].The majority of dimers are formed from atoms whose original

attice sites were coplanar with the surface, or nearly so (within0◦), and so the dimer abundance distributions are inherently unin-ormative about bonding arrangements in directions oblique tohe surface plane. Independently of structure, the relative yieldsf AB dimers are also found to be sensitive to the interaction modelsed in the simulations, such that more/less attractive A–B/A–A,–B interactions are associated with high/low relative AB (AA, BB)ields. The most that can be said about the influence of structure ishat dimer formation is weighted in favour of atoms that originaterom sites that are proximate, but not necessarily neighbouring.his characteristic is not informative about immediate atomictructure in homogeneous materials, but could be exploited forhase identification in materials that are heterogenous at nanoscaleimensions.

For a real target, the measured dimer abundance distributionsould be modified due to differences between the A–A and B–Botentials (not examined in this study). The dissimilar angular dis-ributions of sputtered atoms and dimers [24] represent anotherotentially confounding factor in experimental measurements oningle crystal targets. For example, relative sputter yields measuredor a particular emission direction (e.g. in SIMS) need not be repre-

entative of the angle-integrated relative yields. This problem cane mitigated by sample rotation. In an experimental SIMS studyndertaken to detect structural effects, the focus of interest wouldrobably be the abundance distributions of trimer and larger cluster

ience 257 (2011) 8864– 8870 8869

ions. However, in this study, the predicted sputter yields of trimerspecies were found to be too low for meaningful analysis. A MDinvestigation of trimer sputtering from the AB targets used in thisstudy would require simulation of ∼105 projectile impacts in orderto predict disaggregated yields with acceptable statistics.

5. Conclusions

This paper discusses molecular dynamics (MD) simulations ofthe sputtering of artificial AB binary compound targets that wereconstructed using two sets of interatomic potentials. In the sym-metric model, all bonding interactions are equivalent, while in theasymmetric model, the A–B interactions are strengthened at theexpense of the A–A and B–B interactions. The two potentials predictsimilar material properties (density, cohesive energy, bulk modu-lus) for a given simulation target.

The simulations shed light on the influence of (a) surface andbulk structure, and (b) the interatomic potentials, on monomerand dimer sputtering properties. The absolute and relative pre-dicted sputter yields for monomers were found not to be sensitiveto the form (symmetric vs. asymmetric) of the interatomic poten-tial. This result provides justification for theoretical and simulationapproaches that associate a binding energy with each latticesite, rather than describe binding via interatomic potentials. Withrespect to real materials, the discussion in Section 3.1 suggests thatMD simulations based on simple pair potentials, like those usedin this study, can provide a fair description of sputter yields foratomic species, but not for dimer species. The sputtering proper-ties of dimers are evidently sensitive to the form of the potential,not just the site binding strength, e.g. the abundance of AB dimers(relative to other dimers) increased when the asymmetric poten-tial (which attributes a more attractive potential to AB dimers) wasused.

This study finds that most dimers originate from atoms at nearbylattice sites. The nearest-neighbour contribution to AB clusters istypically ∼50%, and may be as low as 30%. There is no evidencethat abundance distributions for dimers are indicative of the tar-get structure, although other sputtering properties (e.g. clusteringrange, depth of origin) do show structure-dependent variations. Asimilar viewpoint advanced three decades ago [40] was describedat the time as being “dangerously rationalistic” [41], but it is difficultto avoid the conclusion that sputtered nearest neighbours consti-tute only a part of the larger dimer yield. It is interesting to notethat a broad clustering distance, and a correlation between abun-dance and cluster binding energies, were both features of a dimersputtering mechanism proposed some years ago for ZnS (wurtzite)on the basis of purely experimental measurements [32].

In this study, the predicted yields of polyatomic clusters, whichare normally more useful than monomer and dimer species for SIMSspeciation analysis, were found to be too low to be informative. Ifthe abundance distributions of polyatomic clusters were (like thoseof monomers and dimers) insensitive to target structure, some tol-erance of the structural disparities that exist between differentsamples of the same compound (e.g. polycrystal facet structure,fluence-dependent amorphization) might be expected. This wouldbe advantageous for SIMS speciation analysis,

References

[1] V.I. Zaporozchenko, M.G. Stepanova, Prog. Surf. Sci. 49 (1995) 155.[2] J.B. Malherbe, Crit. Rev. Solid State Mater. Sci. 19 (1994) 129.[3] I.C. Lyon, J.M. Saxton, S.J. Cornah, Int. J. Mass. Spectrom. Ion Processes 172 (1998)

115.

[4] N.T. Kita, J.M. Huberty, R. Kozdon, B.L. Beard, J.W. Valley, Surf. Interface Anal.

43 (2011) 427.[5] P. Wilhartitz, M. Grasserbauer, Mikrochim. Acta 89 (1986) 313.[6] Z.P. Li, K. Hirokawa, Appl. Surf. Sci. 220 (2003) 136.[7] L. van Vaeck, A. Adriaens, R. Gijbeis, Mass Spectrom. Rev. 18 (1999) 1.

8 face Sc

[[

[[

[

[

[[

[

[[[[

[

[

[[

[

[[[

[[

[[[

[

870 M.A. Karolewski / Applied Sur

[8] H.J. Borg, J.W. Niemantsverdriet, in: J.J. Spivey, A.K. Agarwal (Eds.), Catalysis: ASpecialist Periodical Report, vol. 11, The Royal Society of Chemistry, Cambridge,1994, p. 1.

[9] S. Daolio, B. Facchin, C. Pagura, A. De Battisti, S. Gelosi, Inorg. Chim. Acta 235(1995) 381.

10] C. Plog, L. Wiedmann, A. Benninghoven, Surf. Sci. 67 (1977) 565.11] G.C. Allen, J.M. Dyke, S.J. Harris, J. Chem. Soc. Faraday Trans. 87 (1991)

875.12] M.J. van Craen, F.C. Adams, Surf. Interface Anal. 5 (1983) 239.13] K.D. Klöppel, E. Jegers, G. von Bünau, Int. J. Mass Spectrom. Ion Processes 49

(1983) 11.14] G.J. Vandentop, M.A. Karolewski, R.G. Cavell, Int. J. Mass Spectrom. Ion Processes

89 (1989) 319.15] F. Honda, G.M. Lancaster, Y. Fukuda, J.W. Rabalais, J. Chem. Phys. 69 (1978)

4931.16] C. Plog, W. Gerhard, Surf. Sci. 152/153 (1985) 127.17] H.M. Urbassek, Results of Molecular Dynamics Calculations, in: R. Behrisch,

W. Eckstein (Eds.), Sputtering by Particle Bombardment, Springer, Berlin,2007.

18] R. Smith, S.D. Kenny, D.J. Ramasawmy, Trans. Philos. R. Soc. London A 362 (2004)157.

19] B.J. Garrison, N. Winograd, D.E. Harrison, Phys. Rev. B 18 (1978) 6000.20] B.J. Garrison, Surf. Sci. 114 (1982) 23.

21] H. Gades, H.M. Urbassek, Nucl. Instrum. Methods B 102 (1995) 261.22] P. Sigmund, Sputtering by ion bombardment: theoretical concepts, in: R.

Behrisch (Ed.), Sputtering by Particle Bombardment. I. Physical Sputtering ofSingle Element Solids, Springer-Verlag, Berlin, 1981.

23] T.J. Colla, H.M. Urbassek, Nucl. Instrum. Methods B 152 (1999) 459.

[[[[[

ience 257 (2011) 8864– 8870

24] V.E. Yurasova, S.S. Elovikov, E.Yu. Zykova, J. Surf. Invest. X-ray, Synchrotron.Neutron. Tech. 1 (2007) 328.

25] R. Buhl, A. Preisinger, Surf. Sci. 47 (1975) 344.26] J.F. Ziegler, M.D. Ziegler, J.P. Biersack, Nucl. Instrum. Methods B 268 (2010)

1818.27] M.A. Karolewski, Nucl. Instrum. Methods B 230 (2005) 402, Download site for

Kalypso: http://sites.google.com/site/KalypsoSimulation.28] S.D. Stoddard, J. Comp. Phys. 27 (1977) 291.29] J.E. Jaffe, R. Pandey, M.J. Steel, Phys. Rev. B 47 (1993) 6299.30] B.J. Garrison, N. Winograd, D. Lo, T.A. Tombrello, M.H. Shapiro, D.E. Harrison,

Surf. Sci. 180 (1987) L129.31] J.H. Chen, Y. Chen, Y.Q. Li, Trans. Nonferrous Met. Soc. China 20 (2010) 502.32] S. Nikzad, W.F. Calaway, M.J. Pellin, C.E. Young, D.M. Gruen, T.A. Tombrello,

Formation Mechanism and Yield of Molecules Ejected from ZnS, CdS, and FeS2

during Ion Bombardment, Argonne National Laboratory Technical Report No.ANL/CHM/PP-76357, Argonne, IL, 1994, doi:10.2172/10134182.

33] K. Nordlund, Nucl. Instrum. Methods B 218 (2004) 9.34] R. Kelly, N.Q. Lam, Radiat. Eff. 19 (1973) 39.35] G. Betz, G.K. Wehner, Sputtering of multicomponent materials, in: R. Behrisch

(Ed.), Sputtering by Particle Bombardment. II. Sputtering of Alloys andCompounds, Electron and Neutron Sputtering, Surface Topography, Springer-Verlag, Berlin, 1983.

36] M.H. Shapiro, T.A. Tombrello, Nucl. Instrum. Methods B 84 (1994) 453.

37] F. Karetta, H.M. Urbassek, Appl. Phys. A 55 (1992) 364.38] G. Betz, W. Husinsky, Nucl. Instrum. Methods B 102 (1995) 281.39] R. Smith, D.E. Harrison, B.J. Garrison, Phys. Rev. B 40 (1989) 93.40] N. Winograd, Prog. Solid State Chem. 13 (1981) 285.41] A. Brown, J.C. Vickerman, Surf. Interface Anal. 6 (1984) 1.